Estimating actual evapotranspiration (ETa) rates for different crop types grown in large irrigation schemes is of great importance to improve water use efficiency. To that end, crop types over large irrigation areas can be determined by employing remote sensing techniques coupled with ground truth data. This study aimed to: a) conduct a water balance work by realizing in-situ water balance measurements, b) derive cropping pattern maps, c) acquire daily crop evapotranspiration (ETc), d) generate fully distributed ETa maps by remote sensing, and e) compare ETa estimations with ETc and in-situ water balance. Landsat-7 and -8 satellite data and meteorological data were used to estimate ETa in the Eastern Mediterranean Region of Turkey in the 2021 hydrological year. Crop types were classified using Sentinel 2A-2B satellite images. The change in catchment storage was +67.08 mm with a 3.34% water balance closure error. The correlation between ETa and ETc for irrigated wheat, potato, lettuce, corn-1, peanut-1, soybean-2, and citrus was significant in growing season.

This study assessed the performance of remote sensing and geographic information system techniques for analysing flood events in agricultural areas and estimating flooded areas in agricultural lands. The Berdan Plain in the southern part of Turkey is below sea level and prone to flood events. The flooded agricultural areas were estimated by using Sentinel-2 satellite data for the Berdan Irrigation Scheme from December 2019-January 2020. The flooded area in the old Aynaz marsh was estimated as 486.79 hectares on 9 January 2020, while the total flooded area in the Berdan Irrigation Project was 4,515.58 hectares. Flood volume was calculated as 2.61 hm3 and the highest water level was estimated to be −0.76 metres in the old Aynaz marsh.

Determination of cropping pattern is a very important factor in quantifying irrigation water requirements at a catchment scale. In this regard, remote sensing is a robust tool for generating spatial-temporal variation of crops. This study focuses on crop classification by using remotely sensed data coupled with ground truth data. Therefore, this study aimed at both classifying each crop type and calculating crop evapotranspiration (ETc) based on reference evapotranspiration (ETo) by using the Penman-Monteith evapotranspiration model and crop coefficient (Kc). ETo was estimated by using data from two meteorological stations located in the study area. To this end, this study was conducted in Akarsu Irrigation District (≈95 km2), a sub-catchment in the Lower Seyhan Plain (LSP), in the 2021 hydrological year. Ground truth data were collected in the two growing seasons. The ENVI program was used to classify crop types from Sentinel 2A-2B satellite images with 10-m by 10-m spatial resolution. Image analysis results demonstrated that bare soil and citrus made up more than half of the area in the winter season, while corn and citrus were preponderant in summer. In addition, the total reference evapotranspiration and crop evapotranspiration were about 1308 mm and 890 mm, respectively in the 2021 water year. ETc values for second crop soybean, first crop corn, wheat, and citrus showed agreement with previous studies of direct methods of evapotranspiration in the Cukurova region. Furthermore, research findings led us to conclude that using remotely sensed satellite data in cropping pattern determination is promising in identifying the crops grown in large agricultural lands. Moreover, remote sensing images can be used to classify accurately crops in the winter and summer seasons, and this study has expanded the application value of remotely sensed data in large-scale irrigation schemes.

Taşkın alanının tespit edilmesi çalışmalarında uzaktan algılama yöntemleri sıklıkla kullanılmaktadır. Yağışı meydana getiren bulutların taşkın anında ve sonrasında da devam etmesi optik görüntüleme yapan uyduların taşkın alanını tespit etmesinde yetersiz kalmasına sebep olmakta, bu eksiklik ise radar uyduları ile giderilebilmektedir. Bu çalışmada, taşkın alanının tespit edilmesi ve taşkın sürecinin izlenmesi amacıyla SAR (Sythetic Aperture Radar, Sentetik Açıklıklı Radar) uydularından olan Sentinel-1 uydusunun kullanılma olanakları araştırılmıştır. Çalışma, Aralık 2016-Ocak 2017 tarihleri arasında Mersin ilinde meydana gelen taşkında en çok etkilenen bölgelerden biri olan, Berdan ovasında mevcut eski Aynaz bataklığında yürütülmüştür. Sentinel-1 uydusuna ait, 24.12.2016-28.01.2017 tarihleri arasında bölgeyi kapsayan 12 adet verinin tamamı analiz edilerek taşkının kapladığı alanlar hesaplanmıştır. Ayrıca fotogrametrik haritalardan bu çalışma için üretilen sayısal arazi modeli (DEM) yardımıyla çalışma alanının kot-alan-hacim grafiği çıkarılmıştır. Bu grafik ve hesaplanan taşkın alanları yardımı ile uydu verisinin olduğu her gün için taşkın hacimleri ve taşkın kotları üretilmiş ve grafiklendirilmiştir. Çalışmada, taşkının yayılımının en büyük tarih 05.01.2017 olarak tespit edilmiş, bu tarihte taşkın alanı 715.02 ha ve taşkın hacmi ise 4.23 hm3 olarak bulunmuştur. Çalışma neticesinde, taşkın anında ve sonrasında mevcut kötü hava şartlarından etkilenmeyen Sentinel-1 uydu verilerinin taşkın çalışmalarında kullanılabileceği sonucunu varılmıştır.